# Demonstrate how variables, or arrays thereof, and constraints, or # arrays of constraints, can be added into a problem. Prints the # solution and all attributes/controls of the problem. # # (C) Fair Isaac Corp., 1983-2024 from __future__ import print_function import xpress as xp N = 4 S = range(N) v1 = xp.var(name="v1", lb=0, ub=10, threshold=5, vartype=xp.continuous) v2 = xp.var(name="v2", lb=1, ub=7, threshold=3, vartype=xp.continuous) vb = xp.var(name="vb", vartype=xp.binary) v = [xp.var(name="y{0}".format(i), lb=0, ub=2*N) for i in S] c1 = v1 + v2 >= 5 m = xp.problem(vb, v, v1, v2, c1, # Adds a list of constraints: three single constraints... 2*v1 + 3*v2 >= 5, v[0] + v[2] >= 1, # ... and a set of constraints indexed by all {i in # S: i<N-1} that ranges in Python are from to>= v[i] + 1 for i in S if i < N-1),
               # objective (to be minimized)
               xp.Sum([i*v[i] for i in S]), sense=xp.minimize, name="myprob")

m.optimize()

print("solve status: ", m.attributes.solvestatus.name)
print("solution status: ", m.attributes.solstatus.name)

print("solution:", m.getSolution())